Paper Abstract and Keywords |
Presentation |
2018-12-07 13:00
Feature Selection for Document Classification focused on Support Vector Kota Sakasegawa, Sachio Hirokawa (Kyushu Univ.) AI2018-25 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Feature selection is a well-known approach for improving the prediction performance of document classifcation, where crucial words are selected and used in vectorization of the documents. This paper proposes an improvement of feature selection of [Sakai & Hirokawa 2012] by considering the occurences of words in ths support vectors. We conducted the evaluation of the proposed method on reuter dataset and confirmed that the proposed method yields allmost the same performance with a small number of feature words. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
document classifcation / machine learning / feature selection / SVM / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 350, AI2018-25, pp. 1-4, Dec. 2018. |
Paper # |
AI2018-25 |
Date of Issue |
2018-11-30 (AI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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AI2018-25 |
Conference Information |
Committee |
AI |
Conference Date |
2018-12-07 - 2018-12-08 |
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(See Japanese page) |
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Paper Information |
Registration To |
AI |
Conference Code |
2018-12-AI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Feature Selection for Document Classification focused on Support Vector |
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document classifcation |
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machine learning |
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feature selection |
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SVM |
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1st Author's Name |
Kota Sakasegawa |
1st Author's Affiliation |
Kyushu University (Kyushu Univ.) |
2nd Author's Name |
Sachio Hirokawa |
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Kyushu University (Kyushu Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-12-07 13:00:00 |
Presentation Time |
25 minutes |
Registration for |
AI |
Paper # |
AI2018-25 |
Volume (vol) |
vol.118 |
Number (no) |
no.350 |
Page |
pp.1-4 |
#Pages |
4 |
Date of Issue |
2018-11-30 (AI) |